Neum AI

What Is Neum AI?

Neum AI is a framework for building data infrastructure for Retrieval Augmented Generation (RAG) and Semantic Search, enabling scalable data pipelines with connectors for vector embeddings.

Target Audience of Neum AI

How To Use Neum AI?

Use Neum AI by leveraging its open-source SDKs to configure RAG pipelines. Connect data sources, embedding models, and vector databases, test locally, and deploy to the Neum AI cloud for production scaling.

Core Features of Neum AI

• Open-source SDKs for composing data flows
• Built-in connectors for data sources and vector databases
• Pipeline testing and deployment to Neum AI cloud
• Distributed architecture for embedding billions of data points
• Real-time vector syncing and pipeline scheduling
• Observability tools for monitoring data sync
• Smart retrieval based on data organization and metadata
• Self-improving context quality via feedback
• Governance features for tracking searches and data movements

Use Cases of Neum AI

• Building scalable Retrieval Augmented Generation pipelines
• Creating semantic search indexes from unstructured data
• Real-time data embedding and indexing for dynamic datasets
• Managing large-scale vector databases for AI applications
• Iterating and testing data pipeline configurations

FAQ from Neum AI

Pricing of Neum AI

Neum AI is Paid service

Contact & Company Information of Neum AI